Adaptive grid job scheduling with genetic algorithms

被引:125
作者
Gao, Y [1 ]
Rong, HQ
Huang, JZ
机构
[1] Nanjing Univ, State Key Lab Novel Software Technol, Nanjing 210093, Peoples R China
[2] Univ Hong Kong, Dept Comp Sci, Hong Kong, Hong Kong, Peoples R China
[3] Univ Hong Kong, E Business Technol Inst, Hong Kong, Hong Kong, Peoples R China
来源
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE | 2005年 / 21卷 / 01期
基金
中国国家自然科学基金;
关键词
service Grid; adaptive job scheduling; prediction; genetic algorithms;
D O I
10.1016/j.future.2004.09.033
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
This paper proposes two models for predicting the completion time of jobs in a service Grid. The single service model predicts the completion time of a job in a Grid that provides only one type of service. The multiple services model predicts the completion time of a job that runs in a Grid which offers multiple types of services. We have developed two algorithms that use the predictive models to schedule jobs at both system level and application level. In application-level scheduling, genetic algorithms are used to minimize the average completion time of jobs through optimal job allocation on each node. The experimental results have shown that the scheduling system using the adaptive scheduling algorithms can allocate service jobs efficiently and effectively. (C) 2004 Elsevier B.V. All rights reserved.
引用
收藏
页码:151 / 161
页数:11
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